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https://issues.apache.org/jira/browse/SPARK-11882?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15055842#comment-15055842
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Apache Spark commented on SPARK-11882:
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User 'jacek-lewandowski' has created a pull request for this issue:
https://github.com/apache/spark/pull/10292
> Allow for running Spark applications against a custom coarse grained scheduler
> ------------------------------------------------------------------------------
>
> Key: SPARK-11882
> URL: https://issues.apache.org/jira/browse/SPARK-11882
> Project: Spark
> Issue Type: Wish
> Components: Spark Core, Spark Submit
> Reporter: Jacek Lewandowski
> Priority: Minor
>
> SparkContext makes a decision which scheduler to use according to the Master
> URI. How about running applications against a custom scheduler? Such a custom
> scheduler would just extend {{CoarseGrainedSchedulerBackend}}.
> The custom scheduler would be created by a provided factory. Factories would
> be defined in the configuration like
> {{spark.scheduler.factory.<name>=<factory-class>}}, where {{name}} is the
> scheduler name. {{SparkContext}}, once it learns that master address is not
> for standalone, Yarn, Mesos, local or any other predefined scheduler, it
> would resolve scheme from the provided master URI and look for the scheduler
> factory with the name equal to the resolved scheme.
> For example:
> {{spark.scheduler.factory.custom=org.a.b.c.CustomSchedulerFactory}}
> then Master address would be {{custom://192.168.1.1}}
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